Book Image

Mastering Graphics Programming with Vulkan

By : Marco Castorina, Gabriel Sassone
5 (1)
Book Image

Mastering Graphics Programming with Vulkan

5 (1)
By: Marco Castorina, Gabriel Sassone

Overview of this book

Vulkan is now an established and flexible multi-platform graphics API. It has been adopted in many industries, including game development, medical imaging, movie productions, and media playback. Learning Vulkan is a foundational step to understanding how a modern graphics API works, both on desktop and mobile. In Mastering Graphics Programming with Vulkan, you’ll begin by developing the foundations of a rendering framework. You’ll learn how to leverage advanced Vulkan features to write a modern rendering engine. The chapters will cover how to automate resource binding and dependencies. You’ll then take advantage of GPU-driven rendering to scale the size of your scenes and finally, you’ll get familiar with ray tracing techniques that will improve the visual quality of your rendered image. By the end of this book, you’ll have a thorough understanding of the inner workings of a modern rendering engine and the graphics techniques employed to achieve state-of-the-art results. The framework developed in this book will be the starting point for all your future experiments.
Table of Contents (21 chapters)
1
Part 1: Foundations of a Modern Rendering Engine
7
Part 2: GPU-Driven Rendering
13
Part 3: Advanced Rendering Techniques

Summary

In this chapter, we described how to implement ray-traced reflections. We started with an overview of screen-space reflection, a technique that was used for many years before ray tracing hardware was available. We explained how it works and some of its limitations.

Next, we described our ray tracing implementation to determine reflection values. We provided two methods to determine the reflected ray direction and explained how the reflected color is computed if a hit is returned.

Since we only use one sample per fragment, the result of this step is noisy. To reduce as much of this noise as possible, we implemented a denoiser based on SVGF. This technique consists of three passes. First, there’s a temporal accumulation step to compute color and luminance moments. Then, we compute the luminance variance. Finally, we process the color output by passing it through five iterations of a wavelet filter.

This chapter also concludes our book! We hope you enjoyed reading...